Search results for "accelerators"

Hits ?▲	Authors	Title	Venue	Year	Link
12	Sadiq M. Sait, Aiman El-Maleh, Mohammad Altakrouri, Ahmad Shawahna	Optimization of FPGA-based CNN accelerators using metaheuristics.	J. Supercomput.	2023	DBLP DOI BibTeX RDF
12	Yiming Ouyang, Jiaxin Wang, Chenglong Sun, Qi Wang 0027, Huaguo Liang	URMP: using reconfigurable multicast path for NoC-based deep neural network accelerators.	J. Supercomput.	2023	DBLP DOI BibTeX RDF
12	Peng Li, Rui Hou	Int-Monitor: a model triggered hardware trojan in deep learning accelerators.	J. Supercomput.	2023	DBLP DOI BibTeX RDF
12	Jinyi Xu, Hao Shi, Yixiang Chen	Efficient tasks scheduling in multicore systems integrated with hardware accelerators.	J. Supercomput.	2023	DBLP DOI BibTeX RDF
12	Chengpeng Xia, Yawen Chen 0001, Haibo Zhang 0001, Hao Zhang, Fei Dai, Jigang Wu	Efficient neural network accelerators with optical computing and communication.	Comput. Sci. Inf. Syst.	2023	DBLP DOI BibTeX RDF
12	Paria Darbani, Hakem Beitollahi, Pejman Lotfi-Kamran	Rei: A Reconfigurable Interconnection Unit for Array-Based CNN Accelerators.	IEEE Trans. Emerg. Top. Comput.	2023	DBLP DOI BibTeX RDF
12	Marco Rios, Flavio Ponzina, Alexandre Levisse, Giovanni Ansaloni, David Atienza	Bit-Line Computing for CNN Accelerators Co-Design in Edge AI Inference.	IEEE Trans. Emerg. Top. Comput.	2023	DBLP DOI BibTeX RDF
12	Ourania Spantidi, Georgios Zervakis 0001, Sami Alsalamin, Isai Roman-Ballesteros, Jörg Henkel, Hussam Amrouch, Iraklis Anagnostopoulos	Targeting DNN Inference Via Efficient Utilization of Heterogeneous Precision DNN Accelerators.	IEEE Trans. Emerg. Top. Comput.	2023	DBLP DOI BibTeX RDF
12	Gunjan Rajput, V. Logashree, Kunika Naresh Biyani, Santosh Kumar Vishvakarma	Clock Gating-Based Effectual Realization of Stochastic Hyperbolic Tangent Function for Deep Neural Hardware Accelerators.	Circuits Syst. Signal Process.	2023	DBLP DOI BibTeX RDF
12	Gopal Raut, Jogesh Mukala, Vishal Sharma 0004, Santosh Kumar Vishvakarma	Designing a Performance-Centric MAC Unit with Pipelined Architecture for DNN Accelerators.	Circuits Syst. Signal Process.	2023	DBLP DOI BibTeX RDF
12	Raul Murillo 0001, Alberto A. Del Barrio, Guillermo Botella, Christian Pilato	Generating Posit-Based Accelerators With High-Level Synthesis.	IEEE Trans. Circuits Syst. I Regul. Pap.	2023	DBLP DOI BibTeX RDF
12	Hendrik Wöhrle, Felix Schneider, Fabian Schlenke, Denis Lebold, Mariela De Lucas Alvarez, Frank Kirchner, Michael Karagounis	Multi-Objective Surrogate-Model-Based Neural Architecture and Physical Design Co-Optimization of Energy Efficient Neural Network Hardware Accelerators.	IEEE Trans. Circuits Syst. I Regul. Pap.	2023	DBLP DOI BibTeX RDF
12	Raphael Nägele, Jakob Finkbeiner, Valentin Stadtlander, Markus Grözing, Manfred Berroth	Analog Multiply-Accumulate Cell With Multi-Bit Resolution for All-Analog AI Inference Accelerators.	IEEE Trans. Circuits Syst. I Regul. Pap.	2023	DBLP DOI BibTeX RDF
12	Bai-Kui Yan, Shanq-Jang Ruan	Area Efficient Compression for Floating-Point Feature Maps in Convolutional Neural Network Accelerators.	IEEE Trans. Circuits Syst. II Express Briefs	2023	DBLP DOI BibTeX RDF
12	Leonardo Rezende Juracy, Alexandre M. Amory, Fernando Moraes 0001	A Comprehensive Evaluation of Convolutional Hardware Accelerators.	IEEE Trans. Circuits Syst. II Express Briefs	2023	DBLP DOI BibTeX RDF
12	Wenjie Li 0003, Aokun Hu, Gang Wang, Ningyi Xu, Guanghui He	Low-Complexity Precision-Scalable Multiply-Accumulate Unit Architectures for Deep Neural Network Accelerators.	IEEE Trans. Circuits Syst. II Express Briefs	2023	DBLP DOI BibTeX RDF
12	Stylianos I. Venieris, Christos-Savvas Bouganis, Nicholas D. Lane	Multiple-Deep Neural Network Accelerators for Next-Generation Artificial Intelligence Systems.	Computer	2023	DBLP DOI BibTeX RDF
12	Jingweijia Tan, Liqi Ping, Qixiang Wang, Kaige Yan	Saca-AVF: A Quantitative Approach to Analyze the Architectural Vulnerability Factors of CNN Accelerators.	IEEE Trans. Computers	2023	DBLP DOI BibTeX RDF
12	Shamik Kundu, Suvadeep Banerjee, Arnab Raha, Fei Su, Suriyaprakash Natarajan, Kanad Basu	Trouble-Shooting at GAN Point: Improving Functional Safety in Deep Learning Accelerators.	IEEE Trans. Computers	2023	DBLP DOI BibTeX RDF
12	Hyein Shin, Myeonggu Kang, Lee-Sup Kim	Fault-Free: A Framework for Analysis and Mitigation of Stuck-at-Fault on Realistic ReRAM-Based DNN Accelerators.	IEEE Trans. Computers	2023	DBLP DOI BibTeX RDF
12	Arghadip Das, Chandrachur Majumder, Debaprasad De, Arnab Raha, Mrinal Kanti Naskar	HIPEDAP: Energy-Efficient Hardware Accelerators for Hidden Periodicity Detection.	IEEE Trans. Computers	2023	DBLP DOI BibTeX RDF
12	Chanho Park, Bogil Kim, Sungmin Ryu, William J. Song	NeuroSpector: Systematic Optimization of Dataflow Scheduling in DNN Accelerators.	IEEE Trans. Parallel Distributed Syst.	2023	DBLP DOI BibTeX RDF
12	Lennart Bamberg, Arash Pourtaherian, Luc Waeijen, Anupam Chahar, Orlando Moreira	Synapse Compression for Event-Based Convolutional-Neural-Network Accelerators.	IEEE Trans. Parallel Distributed Syst.	2023	DBLP DOI BibTeX RDF
12	Chunyang Wang, Yuebin Bai, Desen Sun	CD-MSA: Cooperative and Deadline-Aware Scheduling for Efficient Multi-Tenancy on DNN Accelerators.	IEEE Trans. Parallel Distributed Syst.	2023	DBLP DOI BibTeX RDF
12	Siling Yang, Shuibing He, Hexiao Duan, Weijian Chen 0002, Xuechen Zhang 0001, Tong Wu, Yanlong Yin	APQ: Automated DNN Pruning and Quantization for ReRAM-Based Accelerators.	IEEE Trans. Parallel Distributed Syst.	2023	DBLP DOI BibTeX RDF
12	Jude Haris, Perry Gibson, José Cano 0001, Nicolas Bohm Agostini, David R. Kaeli	SECDA-TFLite: A toolkit for efficient development of FPGA-based DNN accelerators for edge inference.	J. Parallel Distributed Comput.	2023	DBLP DOI BibTeX RDF
12	Topi Leppänen, Atro Lotvonen, Panagiotis Mousouliotis, Joonas Multanen, Georgios Keramidas, Pekka Jääskeläinen	Efficient OpenCL system integration of non-blocking FPGA accelerators.	Microprocess. Microsystems	2023	DBLP DOI BibTeX RDF
12	Chenghao Quan, Mohammed E. Fouda, Sugil Lee, Giju Jung, Jongeun Lee, Ahmed M. Eltawil, Fadi J. Kurdahi	Training-Free Stuck-At Fault Mitigation for ReRAM-Based Deep Learning Accelerators.	IEEE Trans. Comput. Aided Des. Integr. Circuits Syst.	2023	DBLP DOI BibTeX RDF
12	Xiandong Zhao, Ying Wang 0001, Cheng Liu 0008, Cong Shi 0003, Kaijie Tu, Lei Zhang 0008	Network Pruning for Bit-Serial Accelerators.	IEEE Trans. Comput. Aided Des. Integr. Circuits Syst.	2023	DBLP DOI BibTeX RDF
12	Dimitrios Danopoulos, Georgios Zervakis 0001, Kostas Siozios, Dimitrios Soudris, Jörg Henkel	AdaPT: Fast Emulation of Approximate DNN Accelerators in PyTorch.	IEEE Trans. Comput. Aided Des. Integr. Circuits Syst.	2023	DBLP DOI BibTeX RDF
12	Yanhong Wang, Zihao Zhao, Xu Jin, Haotian Zheng, Maohua Nie, Qiaosha Zou, Chuanjin Richard Shi	AutoMap: Automatic Mapping of Neural Networks to Deep Learning Accelerators for Edge Devices.	IEEE Trans. Comput. Aided Des. Integr. Circuits Syst.	2023	DBLP DOI BibTeX RDF
12	Yangjie Qi, Shuo Zhang, Tarek M. Taha	TRIM: A Design Space Exploration Model for Deep Neural Networks Inference and Training Accelerators.	IEEE Trans. Comput. Aided Des. Integr. Circuits Syst.	2023	DBLP DOI BibTeX RDF
12	Songyun Qu, Bing Li 0017, Shixin Zhao, Lei Zhang 0008, Ying Wang 0001	A Coordinated Model Pruning and Mapping Framework for RRAM-Based DNN Accelerators.	IEEE Trans. Comput. Aided Des. Integr. Circuits Syst.	2023	DBLP DOI BibTeX RDF
12	Sugil Lee, Mohammed E. Fouda, Jongeun Lee, Ahmed M. Eltawil, Fadi J. Kurdahi	Offline Training-Based Mitigation of IR Drop for ReRAM-Based Deep Neural Network Accelerators.	IEEE Trans. Comput. Aided Des. Integr. Circuits Syst.	2023	DBLP DOI BibTeX RDF
12	Shikhar Tuli, Niraj K. Jha	TransCODE: Co-Design of Transformers and Accelerators for Efficient Training and Inference.	IEEE Trans. Comput. Aided Des. Integr. Circuits Syst.	2023	DBLP DOI BibTeX RDF
12	Azat Azamat, Faaiz Asim, Jintae Kim, Jongeun Lee	Partial Sum Quantization for Reducing ADC Size in ReRAM-Based Neural Network Accelerators.	IEEE Trans. Comput. Aided Des. Integr. Circuits Syst.	2023	DBLP DOI BibTeX RDF
12	Corentin Ferry, Tomofumi Yuki, Steven Derrien, Sanjay V. Rajopadhye	Increasing FPGA Accelerators Memory Bandwidth With a Burst-Friendly Memory Layout.	IEEE Trans. Comput. Aided Des. Integr. Circuits Syst.	2023	DBLP DOI BibTeX RDF
12	Ayush Arunachalam, Shamik Kundu, Arnab Raha, Suvadeep Banerjee, Suriyaprakash Natarajan, Kanad Basu	A Novel Low-Power Compression Scheme for Systolic Array-Based Deep Learning Accelerators.	IEEE Trans. Comput. Aided Des. Integr. Circuits Syst.	2023	DBLP DOI BibTeX RDF
12	Jingbo Zhou, Xinmiao Zhang	Joint Protection Scheme for Deep Neural Network Hardware Accelerators and Models.	IEEE Trans. Comput. Aided Des. Integr. Circuits Syst.	2023	DBLP DOI BibTeX RDF
12	Prachi Shukla, Vasilis F. Pavlidis, Emre Salman, Ayse K. Coskun	TREAD-M3D: Temperature-Aware DNN Accelerators for Monolithic 3-D Mobile Systems.	IEEE Trans. Comput. Aided Des. Integr. Circuits Syst.	2023	DBLP DOI BibTeX RDF
12	Luke Kljucaric, Alan D. George	Deep Learning Inferencing with High-performance Hardware Accelerators.	ACM Trans. Intell. Syst. Technol.	2023	DBLP DOI BibTeX RDF
12	Qiaoyi Liu, Jeff Setter, Dillon Huff, Maxwell Strange, Kathleen Feng, Mark Horowitz, Priyanka Raina, Fredrik Kjolstad	Unified Buffer: Compiling Image Processing and Machine Learning Applications to Push-Memory Accelerators.	ACM Trans. Archit. Code Optim.	2023	DBLP DOI BibTeX RDF
12	Iulian Brumar, Georgios Zacharopoulos, Yuan Yao 0006, Saketh Rama, David Brooks 0001, Gu-Yeon Wei	Early DSE and Automatic Generation of Coarse-grained Merged Accelerators.	ACM Trans. Embed. Comput. Syst.	2023	DBLP DOI BibTeX RDF
12	May Young, Alan J. Hu, Guy G. F. Lemieux	Cache Abstraction for Data Race Detection in Heterogeneous Systems with Non-coherent Accelerators.	ACM Trans. Embed. Comput. Syst.	2023	DBLP DOI BibTeX RDF
12	Chengpeng Xia, Yawen Chen 0001, Haibo Zhang 0001, Jigang Wu	STADIA: Photonic Stochastic Gradient Descent for Neural Network Accelerators.	ACM Trans. Embed. Comput. Syst.	2023	DBLP DOI BibTeX RDF
12	Kalhan Koul, Jackson Melchert, Kavya Sreedhar, Leonard Truong, Gedeon Nyengele, Keyi Zhang, Qiaoyi Liu, Jeff Setter, Po-Han Chen, Yuchen Mei, Maxwell Strange, Ross Daly, Caleb Donovick, Alex Carsello, Taeyoung Kong, Kathleen Feng, Dillon Huff, Ankita Nayak, Rajsekhar Setaluri, James Thomas 0003, Nikhil Bhagdikar, David Durst, Zachary Myers, Nestan Tsiskaridze, Stephen Richardson, Rick Bahr, Kayvon Fatahalian, Pat Hanrahan, Clark W. Barrett, Mark Horowitz, Christopher Torng, Fredrik Kjolstad, Priyanka Raina	AHA: An Agile Approach to the Design of Coarse-Grained Reconfigurable Accelerators and Compilers.	ACM Trans. Embed. Comput. Syst.	2023	DBLP DOI BibTeX RDF
12	Ioannis Tsounis, Dimitris Agiakatsikas, Mihalis Psarakis	A Methodology for Fault-tolerant Pareto-optimal Approximate Designs of FPGA-based Accelerators.	ACM Trans. Embed. Comput. Syst.	2023	DBLP DOI BibTeX RDF
12	Ziyu Wang, Yuting Wu, Yongmo Park, Sangmin Yoo, Xinxin Wang, Jason K. Eshraghian, Wei D. Lu	PowerGAN: A Machine Learning Approach for Power Side-Channel Attack on Compute-in-Memory Accelerators.	Adv. Intell. Syst.	2023	DBLP DOI BibTeX RDF
12	Sayani Majumdar, Ioannis Zeimpekis	Back-End and Flexible Substrate Compatible Analog Ferroelectric Field-Effect Transistors for Accurate Online Training in Deep Neural Network Accelerators.	Adv. Intell. Syst.	2023	DBLP DOI BibTeX RDF
12	Francisco Muñoz-Martínez, José L. Abellán, Manuel E. Acacio, Tushar Krishna	STIFT: A Spatio-Temporal Integrated Folding Tree for Efficient Reductions in Flexible DNN Accelerators.	ACM J. Emerg. Technol. Comput. Syst.	2023	DBLP DOI BibTeX RDF
12	Xiangru Chen, Maneesh Merugu, Jiaqi Zhang 0002, Sandip Ray	AroMa: Evaluating Deep Learning Systems for Stealthy Integrity Attacks on Multi-tenant Accelerators.	ACM J. Emerg. Technol. Comput. Syst.	2023	DBLP DOI BibTeX RDF
12	Shanshi Huang, Hongwu Jiang, Shimeng Yu	Hardware-aware Quantization/Mapping Strategies for Compute-in-Memory Accelerators.	ACM Trans. Design Autom. Electr. Syst.	2023	DBLP DOI BibTeX RDF
12	Yifan Qin, Zheyu Yan, Wujie Wen, Xiaobo Sharon Hu, Yiyu Shi 0001	Negative Feedback Training: A Novel Concept to Improve Robustness of NVCiM DNN Accelerators.	CoRR	2023	DBLP DOI BibTeX RDF
12		HADES: Hardware/Algorithm Co-design in DNN accelerators using Energy-efficient Approximate Alphabet Set Multipliers.	CoRR	2023	DBLP DOI BibTeX RDF
12	Muhammad Abdullah Hanif, Muhammad Shafique 0001	FAQ: Mitigating the Impact of Faults in the Weight Memory of DNN Accelerators through Fault-Aware Quantization.	CoRR	2023	DBLP DOI BibTeX RDF
12	Richard Sattel, Christoph Spang 0001, Carsten Heinz, Andreas Koch 0001	PQC-HA: A Framework for Prototyping and In-Hardware Evaluation of Post-Quantum Cryptography Hardware Accelerators.	CoRR	2023	DBLP DOI BibTeX RDF
12	Georg Rutishauser, Robin Hunziker, Alfio Di Mauro, Sizhen Bian, Luca Benini, Michele Magno	ColibriES: A Milliwatts RISC-V Based Embedded System Leveraging Neuromorphic and Neural Networks Hardware Accelerators for Low-Latency Closed-loop Control Applications.	CoRR	2023	DBLP DOI BibTeX RDF
12	Zhewen Yu, Christos-Savvas Bouganis	AutoWS: Automate Weights Streaming in Layer-wise Pipelined DNN Accelerators.	CoRR	2023	DBLP DOI BibTeX RDF
12	Trevor E. Pogue, Nicola Nicolici	Fast Inner-Product Algorithms and Architectures for Deep Neural Network Accelerators.	CoRR	2023	DBLP DOI BibTeX RDF
12	Hans Johnson, Tianyang Fang, Alejandro Perez-Vicente, Jafar Saniie	Reconfigurable Distributed FPGA Cluster Design for Deep Learning Accelerators.	CoRR	2023	DBLP DOI BibTeX RDF
12	Jinming Zhuang, Jason Lau, Hanchen Ye, Zhuoping Yang, Yubo Du, Jack Lo, Kristof Denolf, Stephen Neuendorffer, Alex K. Jones, Jingtong Hu, Deming Chen, Jason Cong, Peipei Zhou 0001	CHARM: Composing Heterogeneous Accelerators for Matrix Multiply on Versal ACAP Architecture.	CoRR	2023	DBLP DOI BibTeX RDF
12	Mingi Yoo, Jaeyong Song, Hyeyoon Lee, Jounghoo Lee, Namhyung Kim, Youngsok Kim, Jinho Lee	Slice-and-Forge: Making Better Use of Caches for Graph Convolutional Network Accelerators.	CoRR	2023	DBLP DOI BibTeX RDF
12	Sourjya Roy, Cheng Wang, Anand Raghunathan	Evaluation of STT-MRAM as a Scratchpad for Training in ML Accelerators.	CoRR	2023	DBLP DOI BibTeX RDF
12	Bharath Srinivas Prabakaran, Vojtech Mrazek, Zdenek Vasícek, Lukás Sekanina, Muhammad Shafique 0001	autoXFPGAs: An End-to-End Automated Exploration Framework for Approximate Accelerators in FPGA-Based Systems.	CoRR	2023	DBLP DOI BibTeX RDF
12	Nandeeka Nayak, Toluwanimi O. Odemuyiwa, Shubham Ugare, Christopher W. Fletcher, Michael Pellauer, Joel S. Emer	TeAAL: A Declarative Framework for Modeling Sparse Tensor Accelerators.	CoRR	2023	DBLP DOI BibTeX RDF
12	Zheyu Yan, Xiaobo Sharon Hu, Yiyu Shi 0001	Compute-in-Memory based Neural Network Accelerators for Safety-Critical Systems: Worst-Case Scenarios and Protections.	CoRR	2023	DBLP DOI BibTeX RDF
12	James Timothy Meech, Vasileios Tsoutsouras, Phillip Stanley-Marbell	The Data Movement Bottleneck: Theoretical Shortcomings of Analog Optical Fourier Transform and Convolution Computing Accelerators.	CoRR	2023	DBLP DOI BibTeX RDF
12	Lakshmi Nair, David Widemann, Brad Turcott, Nick Moore, Alexandra Wleklinski, Darius Bunandar, Ioannis Papavasileiou, Shihu Wang, Eric Logan	Photonic Accelerators for Image Segmentation in Autonomous Driving and Defect Detection.	CoRR	2023	DBLP DOI BibTeX RDF
12	Pablo Antonio Martínez, Jackson Woodruff, Jordi Armengol-Estapé, Gregorio Bernabé, José Manuel García 0001, Michael F. P. O'Boyle	Matching Linear Algebra and Tensor Code to Specialized Hardware Accelerators.	CoRR	2023	DBLP DOI BibTeX RDF
12	Xueying Wu, Edward Hanson, Nansu Wang, Qilin Zheng, Xiaoxuan Yang, Huanrui Yang, Shiyu Li, Feng Cheng, Partha Pratim Pande, Janardhan Rao Doppa, Krishnendu Chakrabarty, Hai Li 0001	Block-Wise Mixed-Precision Quantization: Enabling High Efficiency for Practical ReRAM-based DNN Accelerators.	CoRR	2023	DBLP DOI BibTeX RDF
12	Murali Emani, Sam Foreman, Varuni Sastry, Zhen Xie, Siddhisanket Raskar, William Arnold, Rajeev Thakur, Venkatram Vishwanath, Michael E. Papka	A Comprehensive Performance Study of Large Language Models on Novel AI Accelerators.	CoRR	2023	DBLP DOI BibTeX RDF
12	Hamid Farzaneh, João Paulo Cardoso de Lima, Mengyuan Li, Asif Ali Khan, Xiaobo Sharon Hu, Jerónimo Castrillón	C4CAM: A Compiler for CAM-based In-memory Accelerators.	CoRR	2023	DBLP DOI BibTeX RDF
12	Jianyi Cheng, Cheng Zhang, Zhewen Yu, Alexander Montgomerie-Corcoran, Can Xiao, Christos-Savvas Bouganis, Yiren Zhao	Fast Prototyping Next-Generation Accelerators for New ML Models using MASE: ML Accelerator System Exploration.	CoRR	2023	DBLP DOI BibTeX RDF
12	Ziyu Wang, Yuting Wu, Yongmo Park, Sangmin Yoo, Xinxin Wang, Jason K. Eshraghian, Wei D. Lu	PowerGAN: A Machine Learning Approach for Power Side-Channel Attack on Compute-in-Memory Accelerators.	CoRR	2023	DBLP DOI BibTeX RDF
12	Filippo Minnella, Teodoro Urso, Mihai T. Lazarescu, Luciano Lavagno	Design and Optimization of Residual Neural Network Accelerators for Low-Power FPGAs Using High-Level Synthesis.	CoRR	2023	DBLP DOI BibTeX RDF
12	Yuto Nishida, Sahil Bhatia, Shadaj Laddad, Hasan Genc, Yakun Sophia Shao, Alvin Cheung	Code Transpilation for Hardware Accelerators.	CoRR	2023	DBLP DOI BibTeX RDF
12	Antonin Sulc, Raimund Kammering, Annika Eichler, Tim Wilksen	PACuna: Automated Fine-Tuning of Language Models for Particle Accelerators.	CoRR	2023	DBLP DOI BibTeX RDF
12	Nivedita Shrivastava, Smruti R. Sarangi	SparseLock: Securing Neural Network Models in Deep Learning Accelerators.	CoRR	2023	DBLP DOI BibTeX RDF
12	Hadi Esmaeilzadeh, Soroush Ghodrati, Andrew B. Kahng, Joon Kyung Kim, Sean Kinzer, Sayak Kundu, Rohan Mahapatra, Susmita Dey Manasi, Sachin S. Sapatnekar, Zhiang Wang, Ziqing Zeng	An Open-Source ML-Based Full-Stack Optimization Framework for Machine Learning Accelerators.	CoRR	2023	DBLP DOI BibTeX RDF
12	Xiaobei Yan, Han Qiu 0001, Tianwei Zhang 0004	A Unified Hardware-based Threat Detector for AI Accelerators.	CoRR	2023	DBLP DOI BibTeX RDF
12	Kaustubh Shivdikar	Enabling Accelerators for Graph Computing.	CoRR	2023	DBLP DOI BibTeX RDF
12	Anna Lena Duque Antón, Johannes Müller, Lucas Deutschmann, Mohammad Rahmani Fadiheh, Dominik Stoffel, Wolfgang Kunz	A Golden-Free Formal Method for Trojan Detection in Non-Interfering Accelerators.	CoRR	2023	DBLP DOI BibTeX RDF
12	Kishansingh Rajput, Malachi Schram, Karthik Somayaji N. S.	Uncertainty Aware Deep Learning for Particle Accelerators.	CoRR	2023	DBLP DOI BibTeX RDF
12	Sean Kinzer, Soroush Ghodrati, Rohan Mahapatra, Byung Hoon Ahn, Edwin Mascarenhas, Xiaolong Li, Janarbek Matai, Liang Zhang, Hadi Esmaeilzadeh	Restoring the Broken Covenant Between Compilers and Deep Learning Accelerators.	CoRR	2023	DBLP DOI BibTeX RDF
12	Mingi Yoo, Jaeyong Song, Jounghoo Lee, Namhyung Kim, Youngsok Kim, Jinho Lee	SGCN: Exploiting Compressed-Sparse Features in Deep Graph Convolutional Network Accelerators.	CoRR	2023	DBLP DOI BibTeX RDF
12	Jingwei Cai, Zuotong Wu, Sen Peng, Yuchen Wei, Zhanhong Tan, Guiming Shi, Mingyu Gao 0001, Kaisheng Ma	Gemini: Mapping and Architecture Co-exploration for Large-scale DNN Chiplet Accelerators.	CoRR	2023	DBLP DOI BibTeX RDF
12	Dhireesha Kudithipudi, Anurag Reddy Daram, Abdullah M. Zyarah, Fatima Tuz Zohora, James B. Aimone, Angel Yanguas-Gil, Nicholas Soures, Emre Neftci, Matthew Mattina, Vincenzo Lomonaco, Clare D. Thiem, Benjamin R. Epstein	Design Principles for Lifelong Learning AI Accelerators.	CoRR	2023	DBLP DOI BibTeX RDF
12	Steven Shaw, Kanishka Tyagi, Shan Zhang	Teacher-Student Knowledge Distillation for Radar Perception on Embedded Accelerators.	CoRR	2023	DBLP DOI BibTeX RDF
12	Tzu-Chien Hsueh, Yeshaiahu Fainman, Bill Lin 0001	ChatGPT at the Speed of Light: Optical Comb-Based Monolithic Photonic-Electronic Linear-Algebra Accelerators.	CoRR	2023	DBLP DOI BibTeX RDF
12	Manos Pavlidakis, Stelios Mavridis, Antony Chazapis, Giorgos Vasiliadis, Angelos Bilas	Arax: A Runtime Framework for Decoupling Applications from Heterogeneous Accelerators.	CoRR	2023	DBLP DOI BibTeX RDF
12	Jiaqi Zhai, Zhaojie Gong, Yueming Wang, Xiao Sun, Zheng Yan 0007, Fu Li, Xing Liu	Revisiting Neural Retrieval on Accelerators.	CoRR	2023	DBLP DOI BibTeX RDF
12	Yehonatan Fridman, Guy Tamir, Gal Oren 0001	Portability and Scalability of OpenMP Offloading on State-of-the-art Accelerators.	CoRR	2023	DBLP DOI BibTeX RDF
12	Ilkin Aliyev, Kama Svoboda, Tosiron Adegbija	Design Space Exploration of Sparsity-Aware Application-Specific Spiking Neural Network Accelerators.	CoRR	2023	DBLP DOI BibTeX RDF
12	Mohammad Hasan Ahmadilivani, Mario Barbareschi, Salvatore Barone, Alberto Bosio, Masoud Daneshtalab, Salvatore Della Torca, Gabriele Gavarini, Maksim Jenihhin, Jaan Raik, Annachiara Ruospo, Ernesto Sánchez 0001, Mahdi Taheri	Special Session: Approximation and Fault Resiliency of DNN Accelerators.	CoRR	2023	DBLP DOI BibTeX RDF
12	Xiaochen Hao, Zijian Ding, Jieming Yin, Yuan Wang 0001, Yun Liang 0001	ALEGO: Towards Cost-Aware Architecture and Integration Co-Design for Chiplet-based Spatial Accelerators.	CoRR	2023	DBLP DOI BibTeX RDF
12	Nikolaos Louloudakis, Perry Gibson, José Cano 0001, Ajitha Rajan	MutateNN: Mutation Testing of Image Recognition Models Deployed on Hardware Accelerators.	CoRR	2023	DBLP DOI BibTeX RDF
12	Xiaoming Chen	Instruction Set Architecture (ISA) for Processing-in-Memory DNN Accelerators.	CoRR	2023	DBLP DOI BibTeX RDF
12	Xiaobei Yan, Chip-Hong Chang, Tianwei Zhang 0004	Defense against ML-based Power Side-channel Attacks on DNN Accelerators with Adversarial Attacks.	CoRR	2023	DBLP DOI BibTeX RDF
12	Midia Reshadi, David Gregg	Maple: A Processing Element for Row-Wise Product Based Sparse Tensor Accelerators.	CoRR	2023	DBLP DOI BibTeX RDF
12	Amr Elsharkawy, Xiao-Ting Michelle To, Philipp Seitz, Yanbin Chen, Yannick Stade, Manuel Geiger, Qunsheng Huang, Xiaorang Guo, Muhammad Arslan Ansari, Christian B. Mendl, Dieter Kranzlmüller, Martin Schulz 0001	Integration of Quantum Accelerators with High Performance Computing - A Review of Quantum Programming Tools.	CoRR	2023	DBLP DOI BibTeX RDF